Approximately 500,000 hip and knee replacements are performed each year in the United States. Although these implants exhibit excellent response during the initial rehabilitation period, fatigue and wear limits their success for long-term operation. Monitoring of fatigue and wear has been previously shown to increase implant longevity by preventing mechanical failure through early intervention. Mechanical fatigue is the accumulation of damage in a structure under applied fluctuating stresses. Though the magnitudes of the applied stresses are less than the tensile strength of the material, the progressive fatigue damage may lead ultimately to mechanical failure. Fatigue life is defined as the number of load cycles necessary to induce failure and it depends on the level of fluctuating strain in the structure. Several fatigue prediction algorithms (e.g. Palmgren-Miner linear rule) rely on counting the number and magnitude of loading cycles applied to a structure. The fatigue in the structure can then be estimated using the cumulative statistics of these applied loads.
Piezoelectric transducers not only provide a mechanism for sensing fatigue in a structure but also can be used for self-powering of the sensors. Piezoelectric based self-powering for medical implants has several advantages over traditional battery powered techniques which suffer from limited life and complications due to biocompatibility. Poly-vinylidene diflouride (PVDF) is a piezoelectric plastic that is currently used for suture materials and has proven to be biocompatible. One disadvantage of PVDF is its very low mechano-electrical energy conversion. Such low power levels pose several challenges for designing self-powered sensors, which include:                1. Self-powered computation: Energy to perform sensing and computation on the sensor has to be harvested from the converted mechanical signal.        2. Non-volatile storage: All the parameters of internal state variables (intermediate and final) have to be stored on a non-volatile memory to account for unavailability of power (i.e. blackouts).        3. Sub-microwatt operation: All computation and storage functions have to be performed at sub-microwatt power dissipation levels to meet the power budget requirement of 1 μW.        
Although many fatigue prediction algorithms mainly rely on the statistics of strain level crossings, it is well known that strain-rates experienced by a mechanical structure also play an important role in predicting fatigue. This is particularly important under high impact conditions during the usage of a biomechanical implant. Thus, it would beneficial to have a self-powered sensor capable of measuring the strain-rates experienced by a mechanical structure.
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.